Epidemic surveillance in a low resource setting: lessons from an evaluation of the Solomon Islands syndromic surveillance system, 2017

Abstract

BackgroundSolomon Islands is one of the least developed countries in the world. Recognising that timely detection of outbreaks is needed to enable early and effective response to disease outbreaks, the Solomon Islands government introduced a simple syndromic surveillance system in 2011. We conducted the first evaluation of the system and the first exploration of a national experience within the broader multi-country Pacific Syndromic Surveillance System to determine if it is meeting its objectives and to identify opportunities for improvement.MethodsWe used a multi-method approach involving retrospective data collection and statistical analysis, modelling, qualitative research and observational methods.ResultsWe found that the system was well accepted, highly relied upon and designed to account for contextual limitations. We found the syndromic algorithm used to identify outbreaks was moderately sensitive, detecting 11.8% (IQR: 6.3–25.0%), 21.3% (IQR: 10.3–36.8%), 27.5% (IQR: 12.8–52.3%) and 40.5% (IQR: 13.5–65.7%) of outbreaks that caused small, moderate, large and very large increases in case presentations to health facilities, respectively. The false alert rate was 10.8% (IQR: 4.8–24.5%). Rural coverage of the system was poor. Limited workforce, surveillance resourcing and other ‘upstream’ health system factors constrained performance.ConclusionsThe system has made a significant contribution to public health security in Solomon Islands, but remains insufficiently sensitive to detect small-moderate sized outbreaks and hence should not be relied upon as a stand-alone surveillance strategy. Rather, the system should sit within a complementary suite of early warning surveillance activities including event-based, in-patient- and laboratory-based surveillance methods. Future investments need to find a balance between actions to address the technical and systems issues that constrain performance while maintaining simplicity and hence sustainability.Electronic supplementary materialThe online version of this article (10.1186/s12889-018-6295-7) contains supplementary material, which is available to authorized users.

Timely detection of Pertussis outbreaks in Iran: The comparison performance of Wavelet-based outbreak detector, Exponential weighted moving average, and Poisson regression-based methods

“…As a result of an increase in the amount of K, the probability of generation alarm on the first day of outbreaks decreased due to an increase in the level of alarm thresholds. The median, minimum and maximum timeliness (according to day) in Haar (k; 0.5) and db10 (k: 0.5) wavelets based method was 2 (1 to 14) and 2 (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14) respectively. This amount was less than the median timeliness of other algorithms.…”

“…Due to many restrictions of the traditional surveillance system in early detection of the outbreak, the syndrome surveillance system is recommended to be used in such conditions. The syndrome surveillance includes collection, analysis, interpretation, and dissemination of health-related data defined in public health sectors (5)(6)(7). The objective of the syndrome surveillance system is to provide an early warning (system) for public health threats in near-real-time (8).…”

Citizen science as a tool for arboviral vector surveillance in a resourced-constrained setting: results of a pilot study in Honiara, Solomon Islands, 2019

“…1 ). The country’s population of 695,000 are dispersed over 992 islands and atolls; 78% reside in rural areas [ 27 ]. The pilot study was undertaken in Honiara, the capital of Solomon Islands.…”

Status and Performance of the Disease Surveillance System in Cagayan Valley, Philippines

“…In 2019, the Philippines reported outbreaks of dengue, diphtheria, measles, and polio (Wolfe et al, 2021). In the region, eight Japanese encephalitis cases were recorded in Nueva Vizcaya in 2017 (Gallardo et al, 2015), also in 2019, it was reported that a measles outbreak was declared in 4 of 5 provinces (Craig et al, 2018), and in August of the same year, dengue outbreak has been declared in 11 towns which prompted the local health officials to recommend that these areas be placed under a state of calamity (Smith, 2015). Emerging and re-emerging epidemics continue to pose tremendous threats to public health even with medical advances and the availability of vaccines.…”